Papers by Matt Grenander
Countering the Effects of Lead Bias in News Summarization via Multi-Stage Training and Auxiliary Losses (D19-1)
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| Challenge: | Sentence position is a strong feature for news summarization, since the lead often summarizes the key points of the article. |
| Approach: | They propose two techniques to make neural systems sensitive to the importance of content in different parts of the article by using random shuffled sentences to pretrain the model. |
| Outcome: | The proposed techniques improve the performance of a competitive reinforcement learning based extractive system, with the auxiliary loss being more powerful than pretraining. |
Sentence-Incremental Neural Coreference Resolution (2022.emnlp-main)
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| Challenge: | Existing systems for identifying spans as mentions are based on mention-pair formulations, but they are not generalized beyond pronouns. |
| Approach: | They propose a sentence-incremental neural coreference resolution system which incrementally builds clusters after marking mention boundaries in a shift-reduce method. |
| Outcome: | The proposed system outperforms state-of-the-art methods on OntoNotes and CODI-CRAC 2021 datasets and is comparable to state- of-the art methods. |